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Science, Engineering Management and Information Technology

6th International Conference, SEMIT 2026, Ankara, Turkey, September 16–18, 2026, Proceedings, Part I

Medium: Buch
ISBN: 978-3-032-39707-2
Verlag: Springer
Erscheinungstermin: 26.10.2026
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The 4-volume set CCIS 3163–3166 constitutes the proceedings of the 6th International Conference on Science, Engineering Management and Information Technology, SEMIT 2026, held in Ankara, Turkey, during September 16–18, 2026.

The 114 full papers and 2 short papers included in the proceedings were carefully reviewed and selected from 205 submissions. They were organized in topical sections as follows:

Part I: Foundation Models, Machine Learning, and AI Architectures; Intelligent Networks, Edge, Cloud, and Distributed Computing; Quantum Computing, Quantum Communication, and Emerging Architectures;

Part II: Cybersecurity, Privacy, Trust, and Resilient Systems; Computer Vision, Remote Sensing, UAVs, and Intelligent Detection; AI in Healthcare, Bioinformatics, and Clinical Decision Support; Digital Education, Human–Computer Interaction, and Cultural Heritage;

Part III: Digital Business, Public Policy, and Organizational Transformation; Intelligent Logistics and Urban Systems; Intelligent Enterprise Systems and Industrial Digitalization; and Intelligent Engineering, Energy, and Smart Infrastructure;

Part IV: Digital Governance, AI Policy, and Intelligent Information Systems; AI Governance, Digital Trust, and Intelligent Systems; and Smart Materials, Sustainable Technologies, and Digital Innovation.

Produkteigenschaften

  • Artikelnummer: 9783032397072
  • Medium: Buch
  • ISBN: 978-3-032-39707-2
  • Verlag: Springer
  • Erscheinungstermin: 26.10.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Communications in Computer and Information Science
  • Produktform: Kartoniert
  • Seiten: 706
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt

Themen

Autoren/Hrsg.

Herausgeber

.- Foundation Models, Machine Learning, and AI Architectures.
.- Community detection in social networks.
.- Federated Generative AI for Privacy-Preserving Large-Scale Model Training at the Edge.
.- Multimodal AI Architectures for Real-Time Decision-Making in Autonomous Systems.
.- Aligning Large Language Models with Human Values from Prompt Engineering to Value Embedding.
.- Adaptive Federated Learning for Sustainable Edge AI: A Lifelong Continual Learning Framework.
.- Next-Generation Hybrid Symbolic–Neural Architectures for Trustworthy and Explainable AI in High-Stakes Domains.
.- Towards AI-Augmented Software Engineering Automated Code Generation, Formal Verification, and Sustainable Maintenance.
.- Toward Robust Multilingual AI: A Multidimensional Benchmark of Few-Shot and Zero-Shot Learning.
.- Validation-Controlled Model Selection and Soft Ensembling for Imbalanced Software Defect Prediction: A Repeated Within- and Cross-Project Evaluation.
.- An Explainable and Counterfactual Framework for Manipulative Language Analysis in Conversational AI.
.- A New Improved Monte Carlo Metropolis-Hastings Framework for Intermittent Demand Forecasting.
.- Intelligent Networks, Edge, Cloud, and Distributed Computing.
.- Energy-Efficient Deep Neural Networks for Sustainable and Intelligent Edge Computing.
.- Designing Scalable Trust Metrics for Autonomous Multi-Agent Systems in Decentralized Networks.
.- AI-Native Wireless Network Management in 6G and Beyond: Architectures, Challenges, and Prospects.
.- Reimagining Internet Architectures with AI-Enabled Semantic Communication.
.- Evolutionary Intelligence-Based Routing for Ultra-Dense IoT Systems.
.- A Systems-Level Evaluation of Serverless Architectures in Mission-Critical Environments.
.- Trusted AI Workflow Orchestration Through Blockchain-Integrated Cloud Computing.
.- Multi-Objective Scheduling and Allocation for Green and Energy-Aware Cloud Infrastructures.
.- Deep Learning-Based Signal Detection and Anti-Jamming Techniques for Space Communication Systems.
.- Quantum Computing, Quantum Communication, and Emerging Architectures.
.- Harnessing Quantum Advantage for Optimization Beyond Shor and Grover.
.- Hybrid Quantum–Classical Pipelines for Big Data Analytics: Workflow Design with Resource and Throughput Analyses.
.- Error-Corrected Quantum Machine Learning in Financial Forecasting.
.- Securing Quantum-Safe Networks: A Comparative Analysis of Post-Quantum, Hybrid, and QKD-Assisted Protocols.
.- Benchmarking the Energy Efficiency of Quantum Neural Networks for Computational Workloads.
.- Neuromorphic and Quantum-Inspired Computing: Toward Next-Generation Artificial Intelligence.
.- Photonic Quantum Chips Enabling Scalable Quantum Cloud Architectures.
.- Hybrid Cryogenic–Quantum Memories Enabling Stable and Long-Lived Quantum Storage.
.- Quantum-Secure Multi-Party Computation Models for Privacy-Preserving Decentralized Finance.
.- Beyond Qubits Integrating Topological Phases and Spintronic Dynamics Toward Quantum Supremacy.
.- AI-driven error mitigation in noisy intermediate-scale quantum (NISQ) devices for physical simulations.